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Verge (pdf with some notes)

Some Context for Thinking About
Technology and Sustainability. A version of my "Towards a Global Brain" talk with a focus on sustainability, given at the Verge conference on the convergence of buildings, transportation, energy, and information, on March 15, 2012.

The Google Autonomous VehicleFriday, July
20, 12Some of you may have heard last year that Google announced a robotic car that has driven over a hundred thousand miles in ordinary traffic.This is thought provoking on a number oflevels. Let’s talk through a number of them, and the implications for our business.

2005: Seven Miles in Seven
HoursFriday, July 20, 12You see, back in 2005, when a car won the DARPA Grand Challenge, it went seven miles in seven hours.

But it isn’t just better
AI “We don’t have better algorithms. We just have more data.” - Peter Norvig, Chief Scientist, GoogleFriday, July 20, 12Big data and machine learning really are central. Yet here, only six years later, the Google autonomous vehicle has driven hundreds of thousands of miles in ordinary traffic. What’sdifferent? Peter Norvig says that the AI isn’t any better. Google just has more data. What kind of data? It turns out that Google had human drivers drive all those streets in cars thatwere taking pictures, and taking very precise measurements of distances to everything. The car is actually remembering the route that was driven by human drivers at some previoustime. That “memory”, as recorded by the car’s electronic sensors, is stored in the cloud, and helps guide the car. As Peter pointed out, “picking a traffic light out of the ﬁeld of view ofa video camera is a hard AI problem. Figuring out if it’s red or green when you already know it’s there is trivial.”

2. Intelligence Augmentation “The human
mind ... operates by association. With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts, in accordance with some intricate web of trails carried by the cells of the brain. It has other characteristics, of course; trails that are not frequently followed are prone to fade, items are not fully permanent, memory is transitory. Yet the speed of action, the intricacy of trails, the detail of mental pictures, is awe-inspiring beyond all else in nature. Man cannot hope fully to duplicate this mental process artificially, but he certainly ought to be able to learn from it. ... One cannot hope thus to equal the speed and flexibility with which the mind follows an associative trail, but it should be possible to beat the mind decisively in regard to the permanence and clarity of the items resurrected from storage. Consider a future device for individual use, which is a sort of mechanized private file and library. It needs a name, and, to coin one at random, "memex" will do.” – Vannevar Bush, As We May Think, 1945Friday, July 20, 12

AI plus the recorded memory
of augmented humansFriday, July 20, 12Big data and machine learning really are central. Yet here, only six years later, the Google autonomous vehicle has driven hundreds of thousands of miles in ordinary traffic. What’sdifferent? Peter Norvig says that the AI isn’t any better. Google just has more data. What kind of data? It turns out that Google had human drivers drive all those streets in cars thatwere taking pictures, and taking very precise measurements of distances to everything. The car is actually remembering the route that was driven by human drivers at some previoustime. That “memory”, as recorded by the car’s electronic sensors, is stored in the cloud, and helps guide the car. As Peter pointed out, “picking a traffic light out of the ﬁeld of view ofa video camera is a hard AI problem. Figuring out if it’s red or green when you already know it’s there is trivial.”

3. Human-Computer Symbiosis “The hope
is that, in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.” – Licklider, J.C.R., "Man-Computer Symbiosis", IRE Transactions on Human Factors in Electronics, vol. HFE-1, 4-11, Mar 1960. EprintFriday, July 20, 12

A few key assertions §
We are building a network-mediated global mind § It is not skynet § It is us, augmentedFriday, July 20, 12But instead, the global brain is a human-computer symbiosis. The google vehicle is only the latest of a long series of developments that show how we are augmenting ourselves andconnecting ourselves into something bigger. This picture is a routing map of the internet. It’s striking how much it looks like a map of the synapses in a human brain. It’s nowherenear as dense yet, but the imagery alone is suggestive. But there’s a lot more here than just imagery.

Friday, July 20, 12But what’s
different now is the way that electronic media speeds up that process. Using twitter, we can instantly learn about trending topics around the world, and share in theresponses of others.

“Wikipedia is not an encyclopedia.
It is a virtual city, a city whose main export to the world is its encyclopedia articles, but with an internal life of its own.”Friday, July 20, 12Michael Nielsen

Friday, July 20, 12Every wikipedia
entry has a talk page. Here’s a discussion of why they changed the page to be about the Tohoku earthquake rather than the Sendai earthquake. It turns out that’s howit’s referred to in Japan.

“The Wanamaker Problem” “Half the
money I spend on advertising is wasted; the trouble is I dont know which half.” - John Wanamaker (1838-1922)Friday, July 20, 12That leads me to the whole topic of feedback loops. It isn’t just that this information is going mind to mind. We are increasingly taking this information and creating electronicfeedback loops, which might include humans in different ways. Increasingly, technology is solving what we can call “the Wanamaker problem.”

Solving the Wanamaker Problem Beyond
Advertising “Only 1% of healthcare spend now goes to diagnosis. We need to shift from the idea that you do diagnosis at the start, followed by treatment, to a cycle of diagnosis, treatment, diagnosis...as we explore what works.” -Pascale Witz, GE Medical DiagnosticsFriday, July 20, 12We’re now seeing this same idea spread to other areas of the economy. For example, in healthcare, personalized medicine requires new kinds of diagnostic feedback loops.

Friday, July 20, 12In the
city of San Francisco, you’re seeing something similar, where all the parking meters are equipped with sensors, and pricing varies by time of day, and ultimately by demand. I’mcalling these systems of “algorithmic regulation” - they regulate in the same way our body regulates itself, autonomically and unconsciously.

The new skills at the
heart of the collective intelligence revolutionFriday, July 20, 12This shift requires new competencies of companies. The ﬁeld has increasingly come to be called “Data Science” - extracting meaning and services from data - and as you can see, theset of skills that make up this job description are in high demand according to LinkedIn. They are literally going asymptotic.